Introduction to AI and Machine Learning: Understand the basic concepts of AI and how machines learn.

Deep Learning Techniques: Learn how deep learning models work, including neural networks like CNNs (Convolutional Neural Networks) and RNNs (Recurrent Neural Networks).

Generative Models: Explore advanced topics like GANs and VAEs, which are used to create realistic images, music, and more.

Practical Experience: Use popular AI tools like TensorFlow, PyTorch, and Keras to build AI models.

Content Generation: Learn how to make AI generate things like text, art, or even video, using state-of-the-art techniques.

Real-World Projects: Work on projects that simulate real-world problems, such as AI for content creation or even autonomous driving systems.

Freshers can expect a starting salary between 6,00,000 to 8,00,000 annually.

As you gain more experience and expertise, salaries can rise significantly. With a few years of experience, salaries can range from 12,00,000 to 18,00,000 annually.

Generative AI professionals with expertise in advanced techniques like GANs, VAEs, and deep learning can see salaries go well beyond 20,00,000 annually in senior or specialized roles.

With experience, you could grow into roles like AI Research Scientist, Machine Learning Engineer, or even AI Architect.

As you work on more complex AI projects, you will have the opportunity to lead AI teams or become a subject matter expert.

Career advancement is fast in AI, with many organizations promoting top talent into leadership positions.

Generative AI is reshaping industries like entertainment, healthcare, and finance by enabling machines to create new content.

This course covers both the theoretical aspects and practical skills needed to implement these technologies in real-world applications.

Companies are looking for professionals who can develop and apply AI in creative ways, and this course gives you the skills to do that.

AI Research Scientist: Work on developing new algorithms and models in AI.

Machine Learning Engineer: Design and implement machine learning systems and models.

Generative AI Specialist: Focus on developing AI tools that create new content like text, images, or music.

Data Scientist: Use AI techniques to analyze large amounts of data and extract valuable insights.

AI Developer: Build AI-powered applications for industries like gaming, healthcare, and finance.

Tech: Companies like Google, Facebook, and Microsoft are heavily investing in AI research and development.

Healthcare: AI is being used to analyze medical data, develop personalized treatment plans, and assist in diagnostics.

Finance: AI helps in fraud detection, algorithmic trading, and risk management.

Entertainment: AI is used to create content such as movies, music, and video games.

Automotive: AI is essential for developing autonomous driving technology.